Experimental and Theoretical Investigations of a Displacement‐Amplified Torsional Damper

Mao, Huimin; Yan, Xueyuan; Ning, Xiangliang; Shi, Shen

doi:10.1155/2021/3602317

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…The results indicated that the LEFCDs possess an excellent energy dissipating capacity and can provide a variety of mechanical behaviors with different LEFCD parameters. Mao et al designed a displacement-amplified torsional damper (DATD), which uses steel, lead and high-damping rubber [16]. The DATDs can significantly reduce the bending moment and shear force at the beam ends and column ends and delay the development of plasticity at the beam ends.…”

Section: Introductionmentioning

confidence: 99%

Numerical and Theoretical Analyses of Friction-Oval Section Mild Steel Rod Composite Dampers

Yan,

Yang,

Guo

et al. 2023

Buildings

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In order to improve the seismic and energy dissipation capacity of the whole structure, a friction-oval section mild steel rod composite damper (FOSRCD) was proposed, and its working principle was clarified. The finite element analysis of FOSRCD was carried out, and the effects of friction, frequency and displacement on the damper performance were studied. Considering the structural characteristics of FOSRCD and the mechanical models of friction dampers and mild steel rod dampers, the restoring force model of the composite dampers was proposed and compared with the numerical simulation results. The results showed that the FOSRCDs had good performance and could provide stable energy dissipation capacities in both directions, with the energy dissipation coefficient exceeding 2.3 and the equivalent damping ratio exceeding 0.37. The theoretical analysis results were in good agreement with the numerical simulation results, which verified the theoretical restoring force model; the FOSRCDs make full use of the friction energy dissipation and the shear and bending energy dissipations of the mild steel rod. It enables the two dampers to work together to achieve the purpose of multi-stage energy dissipation. FOSRCD’s structure allows it to dissipate energy in both the X- and Y-directions. The composite dampers have a variety of restoring force models and can be utilized in a wide range of practical applications.

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Section: Introductionmentioning

confidence: 99%

Numerical and Theoretical Analyses of Friction-Oval Section Mild Steel Rod Composite Dampers

Yan,

Yang,

Guo

et al. 2023

Buildings

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Seismic analysis of a frame structure equipped with displacement-amplified torsional dampers

et al. 2022

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Non intrusive load identification method based on deep learning

Xia

Zhang

Yan

et al. 2023

3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023)

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The current non-invasive load identification methods have limited recognition range and are prone to increasing time consumption. Therefore, a non-invasive load identification method based on deep learning is proposed. Based on actual recognition requirements and standards, extract recognition features, adopt multi-level processing forms, break through the limitations of recognition range, and set them as multi-level adaptive recognition nodes. We constructed a deep learning non-invasive load identification model and utilized GAGOA multi-objective recognition optimization to achieve non-invasive processing. The test results show that the time consumption of the non-invasive load identification unit obtained by applying the proposed method is controlled below 0.5 seconds, which is shorter. This indicates that the practical application effect of this method is better and has certain practical application value.

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Experimental and Theoretical Investigations of a Displacement‐Amplified Torsional Damper

Cited by 3 publications

References 22 publications

Numerical and Theoretical Analyses of Friction-Oval Section Mild Steel Rod Composite Dampers

Numerical and Theoretical Analyses of Friction-Oval Section Mild Steel Rod Composite Dampers

Seismic analysis of a frame structure equipped with displacement-amplified torsional dampers

Non intrusive load identification method based on deep learning

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